基于数字图像处理技术的爆堆粒度分析土木工程专业论文.docxVIP

基于数字图像处理技术的爆堆粒度分析土木工程专业论文.docx

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哈尔滨工业大学工学硕士学位论文 哈尔滨工业大学工学硕士学位论文 - - II - Abstract Rock blasting fragmentation analysis is very important in a mining indutry. Reasonable blasting parameter can reduce the costs of mining and lessen the subsequent workload, so that the overall efficiency in a mining industry can be greatly improved. Usually, the commonly used methods of fragmentation analysis are sieving, statistics on the rate of big block etc. All these methods have more or less limitations. Based on digital image processing technology and the fractal theory, this paper proposes an image segmentation method based on wavelet resolut ion merge and watershed segmentation algorithm, to make sure that the segmented image is proper for rock blasting fragmentation analys is. Firstly, Photograph scheme is determined according to the site condition, and the digital images information is taken. Photoshop 5 is used to geometrically correct the original digital images. For the original digital images, there are often two kinds of problems for rock blasting fragmentation analys is. O ne is unevenness of gray level in the image, and the othe r is the high level of noise in the image. Fo r these two kinds of questionable images, different image processing methods are used to process the images to make sure that the processed images are suitable for rock fragmentation analys is. For uneven of gray level, brightness reversal and image enhancement techniques are used first, then wavelet resolution merge technique is used. For the image contained high level of noise, the noise is reduced first, and the histogram modification method is used to enhance the image. After that wavelet resolution merge technique is also used for the image with high level of noise. After the digital processing procedure, using either of the methods, the improved watershed segmentation algorithm is used to further process the digital images. The improved watershed segmentation method is proposed, based on correctly marking the objects on the

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